Abstract
Introduction
The risk of breast cancer recurrence has been linked to tumour size, grade, oestrogen (ER) receptor status, and degree of lymph node (LN) involvement. However, the role of these variables in predicting time to relapse is not well defined. This study was designed to identify patient and primary tumour characteristics that predict risk periods for breast cancer recurrence within our institution, to enable more tailored surveillance strategies.
Methods
We retrospectively studied a cohort of 473 patients who presented to The Queen Elizabeth Hospital, Adelaide, Australia, with recurrent breast cancer between 1968 and 2008. Patient and primary tumour characteristics were collected, including age, menopausal status, tumour grade, size, ER and progesterone receptor (PR) status, and LN involvement and modeled against time to relapse using Kaplan–Meier survival curves.
Results
High tumour grade, size ≥20 mm, ER negativity, and PR negativity were shown on univariate analysis to correlate significantly with earlier recurrence (P < 0.0001, P = 0.0012, P = 0.0006, and P = 0.006). Multivariate analysis identified tumour grade and size as significant predictors of timing of relapse after adjustment for other variables. LN involvement, menopausal status, and age did not significantly correlate with earlier recurrence.
Conclusions
High tumour grade and larger size were shown to independently predict earlier breast cancer relapse. While LN involvement increases absolute recurrence risk, our study proposes that it does not influence timing of relapse. Use of these predictors will enable key risk periods for onset of relapse to be characterised according to tumour profile with more appropriate discharge to primary care providers for ongoing surveillance.
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Acknowledgments
This study required no external sources of funding. The authors are grateful to the following people for their help: Mr. Thomas Sullivan and Mr. Stuart Howell at the University of Adelaide Discipline of Public Health for providing statistical support; Ms. Margaret Colbeck, Department of Medicine at The Queen Elizabeth Hospital for maintaining the hospital’s cancer registry database; and Mrs. Teresa Occhiodoro-Scott, B.Sc (Hons), Department of Surgery at The Queen Elizabeth Hospital for her assistance with data collection.
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There are no identified conflicts of interest.
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Danielle J. Fitzpatrick and Christine S. Lai contributed equally to this work.
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Fitzpatrick, D.J., Lai, C.S., Parkyn, R.F. et al. Time to Breast Cancer Relapse Predicted By Primary Tumour Characteristics, Not Lymph Node Involvement. World J Surg 38, 1668–1675 (2014). https://doi.org/10.1007/s00268-013-2397-7
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DOI: https://doi.org/10.1007/s00268-013-2397-7